Noise level estimation method, measurement data processing device and program for processing measurement data

ABSTRACT

In a method for estimating a noise level representing the magnitude of a noise component from measurement data, first waveform data composed of high frequency noise components extracted from assumed noise data are divided into segments so that each section where positive values successively occur or each section where negative values successively occur in the first waveform data is defined as one segment. A segment-width threshold is determined based on the distribution of the widths of the segments. Second waveform data composed of high frequency noise components extracted from measurement data are divided into segments in the same manner. Each segment having a width larger than the threshold is excluded from the segments in the second waveform data, to create a first segment group. The noise level is determined based on the heights or areas of the plurality of segments included in the first segment group.

TECHNICAL FIELD

The present invention relates to a method for estimating the magnitudeof a noise component (noise level) in a chromatogram, spectrum or otherkinds of measurement data composed of a peak component, baselinecomponent and noise component, as well as a device for processing suchmeasurement data and a program for processing measurement data.

BACKGROUND ART

One type of device for analyzing components contained in a liquid sampleis the liquid chromatograph. In a liquid chromatograph, a liquid sampleis carried by a stream of mobile phase and introduced into a column. Thecomponents in the sample are temporally separated within the column andsubsequently detected with a detector, such as an absorptiometer, tocreate a chromatogram. Each component is identified from the position ofa peak on the chromatogram, and the concentration of that component isdetermined from the height or area of that peak (for example, see PatentLiterature 1).

In general, a chromatogram obtained by a measurement can be separatedinto three components, i.e. the peak component, baseline component andnoise component. The magnitude of the peak component changes with theelution of various components contained in the liquid sample, while thatof the baseline component changes due to such factors as a change in thepressure of the pump supplying the mobile phase or a change in theambient temperature (baseline drift). The change of the baselinecomponent is normally slower than that of the peak component or noisecomponent. By comparison, the magnitude of the noise component (noiselevel) fluctuates due to various factors, and its fluctuating amplitudeis considerably high. Therefore, it is difficult to isolate the noisecomponent from the chromatogram.

FIG. 1 shows one example of the waveforms (profiles) of a peak component(a), noise component (b) and their sum (c) as well as the power spectrarespectively obtained by Fourier-transforming those profiles. As can beseen in those power spectra, the peak component is localized within alow frequency band, while the noise component is spread over a widefrequency band.

Accordingly, in order to extract the noise component from achromatogram, high-pass filters which reduce frequency components lowerthan a predetermined frequency have been used. By the filter, the peakcomponent localized within the low frequency band can be mostly removed.As the high-pass filter, for example, a second-order difference filteris used. Using a second-order difference filter as the high-pass filteryields a signal having a similar shape to a profile obtained by thesecond-order differentiation of the chromatogram. Though not shown inFIG. 1, the baseline component is also normally localized within the lowfrequency band and therefore can be mostly removed by the high-passfilter, as with the peak component.

CITATION LIST Patent Literature

Patent Literature 1: JP 7-98270 A

SUMMARY OF INVENTION Technical Problem

As just described, by using a high-pass filter, a considerable portionof the peak component and baseline component can be removed from achromatogram to isolate the noise component. However, it is impossibleto completely isolate the noise component from the other ones.Accordingly, it has been difficult to estimate the noise level in achromatogram with high accuracy by merely using the high-pass filter.This problem becomes particularly noticeable when the peak intensity ofthe chromatogram is high or when there is a large number of peaks.

Although the previous description is concerned with the case of achromatogram, similar problems can also occur in various other kinds ofmeasurement data which contain a peak component, baseline component andnoise component, as in a spectrum obtained in a spectroscopicmeasurement.

The problem to be solved by the present invention is to provide a noiselevel estimation method, measurement data processing device, and programfor processing measurement data by which the noise component containedin measurement data which contain the three components of a peakcomponent, baseline component and noise component can be assuredlyisolated, so that the noise level can be estimated with high accuracy.

Solution to Problem

The first aspect of the present invention developed for solving thepreviously described problem is a method for estimating a noise levelrepresenting the magnitude of a noise component from measurement datacontaining the three components of a peak component, baseline componentand noise component, the method including:

a) extracting, from assumed noise data purely composed of assumed noisefor the measurement data, high frequency noise components by means of ahigh-pass filter which attenuates frequency components lower than apredetermined frequency, dividing first waveform data which are waveformdata of the high frequency noise components into a plurality of segmentsso that each section where positive values successively occur or eachsection where negative values successively occur in the first waveformdata is defined as one segment, or so that each section between a localmaximum and a local minimum neighboring each other in the first waveformdata is defined as one segment, and determining a segment-widththreshold based on the distribution of the widths of the plurality ofsegments;

b) extracting high frequency measurement components from the measurementdata by means of the high-pass filter, and dividing second waveform datawhich are waveform data of the high frequency measurement componentsinto a plurality of segments so that each section where positive valuessuccessively occur or each section where negative values successivelyoccur in the second waveform data is defined as one segment, or so thateach section between a local maximum and a local minimum neighboringeach other in the second waveform data is defined as one segment;

c) excluding each segment having a width larger than the threshold fromthe plurality of segments obtained by dividing the second waveform data,to create a first segment group formed by the remaining segments; and

d) determining the noise level based on the heights or areas of theplurality of segments included in the first segment group.

Examples of data that can be used as the assumed noise data include: aset of data purely composed of colored noise, such as white noise havinga power spectrum whose magnitude is uniform and independent of thefrequency, pink noise having a power spectrum whose magnitude isinversely proportional to the frequency, or brown noise whose having apower spectrum whose magnitude is inversely proportional to the squareof the frequency; and a set of data prepared from actually measurednoise.

The threshold of the widths of the plurality of segments may be defined,for example, as the upper limit value of the distribution of the widthsof the plurality of segments obtained by dividing the first waveformdata, or as the upper limit value of a distribution including apredetermined proportion (e.g. 90%) of those segments.

The estimation of the noise level based on the heights or areas of theplurality of segments included in the first segment group can beachieved, for example, by calculating the average value or median of theheights or areas of those segments.

In the noise level estimation method according to the present invention,the second waveform obtained by extracting high frequency measurementcomponents by using the high-pass filter is divided into a plurality ofsegments. Subsequently, each segment whose width is larger than thesegment-width threshold calculated from assumed noise data is excluded,being identified as a segment which has originated from a componentdifferent from the noise component, i.e. which has originated from thepeak component or baseline component. Therefore, even if a portion ofthe peak component or baseline component passes through the high-passfilter, the segment corresponding to that portion is excluded at thisstage. Thus, the noise component is assuredly isolated from themeasurement data, so that the noise level can be estimated with highaccuracy.

Preferably, the noise level estimation method according to the presentinvention may further include:

e) extracting an outlier from the heights or areas of the plurality ofsegments included in the first segment group by comparing each of theheights or areas with the noise level obtained by the estimation;

f) excluding a segment having the outlier from the plurality of segmentsof the first segment group, to create a second segment group;

g) determining a noise level based on the heights or areas of theplurality of segments included in the second segment group.

By excluding an outlier of the height or area of the segment from theestimation of the noise level in this manner, a segment which hasoriginated from a component different from noise yet has not beenexcluded by a mere comparison of the width can be excluded so as toestimate the noise level with an even higher level of accuracy. Theestimation accuracy of the noise level can be further improved byrepeating the process of removing a segment having an outlier andestimating the noise level until all outliers are removed or until apredetermined number of repetitions is reached.

The noise level estimation method according to the present invention mayalso include:

h) determining, for each of the plurality of segments in the secondwaveform data, a segment position representative of the segmentconcerned;

i) extracting, for each of the plurality of segments in the secondwaveform data, target segments which are segments having theirrespective segment positions located within a predetermined range fromthe segment position of the segment concerned; and

j) determining the noise level at the segment position of the segmentconcerned, based on the heights or areas of the segment concerned andthe target segments.

By estimating, for each of the plurality of segments in the highfrequency measurement data, a noise level for a set of segments locatedwithin a predetermined range from the segment concerned in thepreviously described manner, a local noise level at the segment positionof each segment can be determined.

For example, in a gradient analysis in which measurement conditions aretemporally changed, the noise level may also temporally change. Byestimating, for each of the plurality of segments, the noise level atthe segment position of the segment concerned in the previouslydescribed manner the noise level can be estimated with high accuracyeven in the case where the noise level temporally changes.

The previously described technique of excluding a segment having anoutlier to improve the estimation accuracy of the noise level can alsobe applied in the determination of the noise level at the segmentposition of each segment. The estimation accuracy of the noise level canbe further improved by repeating the process of excluding a segmenthaving an outlier and estimating the noise level until all outliers areremoved or until a predetermined number of repetitions is reached.

The second aspect of the present invention developed for solving thepreviously described problem is a measurement data processing deviceused for estimating a noise level from measurement data containing thethree components of a peak component, baseline component and noisecomponent, the device including:

a) a high-pass filter for attenuating frequency components lower than apredetermined frequency;

b) a storage section for holding a segment-width threshold, thethreshold previously determined by extracting, from assumed noise datapurely composed of assumed noise for the measurement data, highfrequency noise components by means of the high-pass filter, dividingfirst waveform data which are waveform data of the high frequency noisecomponents into a plurality of segments so that each section wherepositive values successively occur or each section where negative valuessuccessively occur in the first waveform data is defined as one segment,or so that each section between a local maximum and a local minimumneighboring each other in the first waveform data is defined as onesegment, and determining the threshold based on the distribution of thewidths of the plurality of segments;

c) a second waveform data acquirer for extracting high frequencymeasurement components from the measurement data by means of thehigh-pass filter, and for acquiring second waveform data which arewaveform data of the high frequency measurement components;

d) a segment divider for dividing the second waveform data into aplurality of segments so that each section where positive valuessuccessively occur or each section where negative values successivelyoccur in the second waveform data is defined as one segment, or so thateach section between a local maximum and a local minimum neighboringeach other in the second waveform data is defined as one segment;

e) a first segment group creator for excluding each segment having awidth larger than the threshold from the plurality of segments obtainedby dividing the second waveform data, to create a first segment group;and

f) a noise level calculator for determining the noise level based on theheights or areas of the plurality of segments included in the firstsegment group.

The third aspect of the present invention developed for solving thepreviously described problem is a program for processing measurementdata, used for estimating a noise level from measurement data containingthe three components of a peak component, baseline component and noisecomponent, the program characterized by making a computer, provided witha storage section for holding a segment-width threshold and a high-passfilter, function as the second waveform acquirer, the segment divider,the first segment group creator and the noise level calculator describedin the second aspect of the present invention.

Advantageous Effects of the Invention

With the noise level estimation method, measurement data processingdevice or program for processing measurement data according to thepresent invention, the noise component contained in measurement datawhich include the three components of a peak component, baselinecomponent and noise component can be assuredly isolated, so that thenoise level can be estimated with high accuracy.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 shows waveforms of a peak component, noise component and theirsum as well as their respective power spectra.

FIG. 2 is a configuration diagram of a measurement data processingdevice according to the first embodiment.

FIG. 3 is a flowchart in a noise level estimation method according tothe first embodiment.

FIG. 4 shows a distribution of the segment width of normal white noiseafter a second-order difference calculation.

FIGS. 5A and 5B are the measurement data and first waveform data in thefirst embodiment, respectively.

FIGS. 6A and 6B illustrate the division into segments and the exclusionof segments in the first embodiment, respectively.

FIG. 7 is a configuration diagram of a measurement data processingdevice according to the second embodiment.

FIG. 8 is a flowchart in a noise level estimation method according tothe second embodiment.

DESCRIPTION OF EMBODIMENTS

Embodiments of the noise level estimation method, measurement dataprocessing device, and program for processing measurement data accordingto the present invention are hereinafter described with reference to theattached drawings. The following embodiments deal with the case ofestimating a noise level which is the magnitude of a noise componentcontained in a chromatogram acquired using a liquid chromatograph.

First Embodiment

FIG. 2 shows the configuration of a measurement data processing device10 according to the first embodiment. The measurement data processingdevice 10 is actually a general-purpose personal computer provided witha central processing unit (CPU) 11, memory 12, display unit (monitor)13, input unit 14, high-pass filter 15, storage section 16 including ahigh-volume storage device (e.g. hard disk), communication interface(com. I/F) 17, and other elements. The measurement data processingdevice 10 can be connected to a liquid chromatograph (not shown) throughthe communication interface 17.

In the storage section 16, a program 18 for processing measurement datais stored in addition to the OS (operating system). Executing thisprogram 18 for processing measurement data makes the CPU 11 function asan assumed noise data creator 18 a, first waveform data creator 18 b,segment divider 18 c, threshold setter 18 d, second waveform datacreator 18 e, first segment group creator 18 f, second segment groupcreator 18 g, and noise level calculator 18 h, all of which will bedescribed later.

The noise level estimation method using the measurement data processingdevice 10 of the present embodiment is hereinafter described withreference to the flowchart of FIG. 3.

Initially, based on a user input, the assumed noise data creator 18 acreates assumed noise data which are purely composed of assumed noisefor measurement data (Step S1). The assumed noise in the presentembodiment is normal white noise. Normal white noise is a type of noisehaving both the characteristics of white noise which has a constantintensity at all frequencies and those of Gaussian noise (normallydistributed noise). The first waveform data creator 18 b creates firstwaveform data which are waveform data of high frequency noise componentsobtained by attenuating low frequency components in the assumed noisedata by using the high-pass filter 15 (Step S2). The high-pass filter 15in the present embodiment is a second-order difference filter. A set ofdata different from those created from the normal white noise may alsobe used as the assumed noise data, such as a set of data created fromcolored noise, such as pink noise or brown noise, or a set of actuallymeasured noise data.

After the first waveform data are created, the segment divider 18 cdivides the first waveform data into a plurality of segments so thateach section where positive values successively occur or each sectionwhere negative values successively occur in the first waveform data isdefined as one segment (Step S3). Then, the threshold setter 18 dcreates a distribution of the widths of those segments (FIG. 4) and setsthe segment-width threshold based on that distribution (Step S4). In thepresent embodiment, the largest value in the distribution of the segmentwidth, i.e. six (arbitrary unit in the time-axis direction), is set asthe threshold, and this value is saved in the storage section 16. Itshould be noted that the threshold set by Steps S1 through S4 can beapplied to a plurality of sets of chromatogram data. Accordingly, bypreviously setting the threshold and saving it in the storage section16, a noise component can be estimated from each of the plurality ofsets of chromatogram data by merely performing Step S6 and subsequentsteps, which will be hereinafter described.

Subsequently, the second waveform data creator 18 e reads measurementdata of a chromatogram previously stored in the storage section 16 (FIG.5A), and creates second waveform data, which are waveform data of highfrequency measurement components, using the high-pass filter 15 (StepS5; FIG. 5B). After the second waveform data are created, the segmentdivider 18 c divides the second waveform data into a plurality ofsegments so that each section where positive values successively occuror each section where negative values successively occur in the secondwaveform data is defined as one segment (Step S6; FIG. 6A). Then, thefirst segment group creator 18 f compares the width of each of thesegments in the second waveform data with the segment-width thresholdwhich has been set from the first waveform data, and excludes eachsegment having a width larger than the threshold, to create a firstsegment group (Step S7; FIG. 6B). Step S7 is a process for excluding apeak component or baseline component based on the fact that a segmentwhich corresponds to a peak component or baseline component that haspassed through the high-pass filter has a larger width than that of asegment which originates from the noise component.

After the first segment group is created, the noise level calculator 18h computes the area of each of the segments included in the firstsegment group and sets the average of the computed areas as thesegment-area reference value. Then, the second segment group creator 18g compares the area of each segment in the first segment group with thesegment area reference value, extracts outliers included within acertain proportion (e.g. 5%) of the total number of the segments indescending order of the difference from the area reference value, andexcludes the segments corresponding to the outliers (Step S8), to createa second segment group (Step S9). For example, the extraction of theoutliers can be achieved, for example, by regarding any value largerthan the average +Nσ of the segment areas of the segments as an outlier(where N is a positive integer, and σ is the unbiased standarddeviation). As for N, a suitable value for each set of measurement datacan be used taking into account the distribution of the segment-areavalues.

The segment-area value may be the median of the distribution of thesegment areas of the segments. In this case, the extraction of theoutliers can be achieved, for example, by regarding any value largerthan the median +M×MAD (median absolute deviation) of the areas of thesegments as an outlier (where M is a positive integer).

The extraction of the outliers can also be achieved by various othermethods, e.g. by extracting any value whose difference from the areareference value is larger than a previously set value.

The process of Steps S7 through S9 is intended for removing theinfluence of a noise component having a singular magnitude caused by anaccidental factor during the measurement. In the process of removing theinfluence of a noise component having a singular magnitude, an extremelysmall area value of the segment may also be treated as an outlier, inwhich case any value which does not fall within the range given by theaverage value ±Nσ of the segment areas, or the median ±M×MAD of thesegment areas, can be regarded as an outlier.

Those steps also remove segments which have originated from a peak orbaseline yet have not been excluded by the process using the thresholdof the width.

After the second segment group is created, the noise level calculatoronce more computes the area of each segment included in the secondsegment group, and sets the average of the computed areas as the segmentarea reference value (Step S10). Then, based on this segment areareference value, the noise level calculator determines whether or not anoutlier exists among the area values of the segments. If no outlierexists (“YES” in Step S11), the noise level calculator computes thenoise level from the latest segment area reference value. If an outlierstill exists (“NO” in Step S11), the extraction and exclusion of anoutlier (Step S8) is once more performed by the second segment groupcreator 18 g to create the second segment group (Step S9), and thesegment area reference value is newly set (Step S10). Such a process isrepeated until all outliers are removed. After that, the noise level iscalculated.

If the value of N or M included in the calculation formula of theboundary value used for the extraction of the outliers is small, it maybe impossible to remove all outliers by the repetition of Steps S8through S10. To deal with such a case, the device may be configured tocalculate the noise level, regardless of whether or not an outlierexists, after the number of repetitions of Steps S8 through S10 hasreached a predetermined number (e.g. five).

The process from Steps S8 through S11 is intended for a high-accuracycalculation of the noise level and is not indispensable for the presentinvention. That is to say, the noise level may be directly calculatedfrom the areas of the segments in the first segment group.

Thus, with the noise level estimation method, measurement dataprocessing device and program for processing measurement data accordingto the first embodiment, even if a portion of the peak component orbaseline component passes through the high-pass filter, the segmentcorresponding to that portion is excluded. Therefore, the noisecomponent can be assuredly isolated from the measurement data, so thatthe noise level can be estimated with high accuracy. Additionally,according to the first embodiment, by excluding an outlier of thesegment area from the estimation of the noise level, a segment which hasoriginated from a component different from noise yet has not beenexcluded by a mere comparison of the width can be excluded, so that thenoise level can be estimated with an even higher level of accuracy. Itshould be noted that, as opposed to the previous example in which thesegment (area) reference value and the noise level are determined basedon the area values of the segments, the segment (height) reference valueand the noise level may be determined from the heights of the segments.

Second Embodiment

FIG. 7 shows the configuration of a measurement data processing device10 a according to the second embodiment. The same components asdescribed in the first embodiment are denoted by the same numerals andwill not be described. In the second embodiment, executing the program181 for processing measurement data makes the CPU 11 function as anassumed noise data creator 18 a, first waveform data creator 18 b,segment divider 18 c, threshold setter 18 d, second waveform datacreator 18 e, first segment group creator 18 f, segment positiondeterminer 18 j, target segment extractor 18 k and noise levelcalculator 18 h, all of which will be described later.

The noise level estimation method using the measurement data processingdevice 10 of the present embodiment is hereinafter described withreference to the flowchart of FIG. 8. The same processes as described inthe first embodiment are denoted by the same numerals and will not bedescribed.

The setting of the segment-width threshold using assumed noise data(Steps 51 through S4) and the creation of the first segment group whichis a set of waveform data of high frequency components (Steps S5 throughS7) are the same as in the first embodiment. The second embodiment ischaracterized by the subsequent Steps S21 through S27.

After the first segment group is created, the segment positiondeterminer 18 j designates, for each of the segments in the firstsegment group, the central position of the segment concerned as thesegment position (Step S21). Subsequently, for one segment (which ishereinafter called the “segment in question”) among those segments, thetarget segment extractor 18 k extracts, as the target segments, one ormore segments having their respective segment positions located within apreciously set range from the segment position of the segment inquestion (Step S22). Then, the noise level calculator 18 h computes thenoise level at the segment position of the segment in question based onthe average (or median or the like) of the areas (or heights) of thetarget segments and the segment in question (Step 25).

Steps S22 through S25 are performed for every segment in the firstsegment group. After the calculation of the noise level at the segmentposition of each segment is completed for all segments (“YES” in StepS26), the noise level at the segment position of each segment excludedfrom the creation of the first segment group (i.e. each segmentoriginating from the peak component or baseline component) isinterpolated (Step S27). The interpolation of the noise level can beperformed by an appropriate method for the mode of change in the noiselevel, such as the linear interpolation or spline interpolation.

Thus, with the noise level estimation method, measurement dataprocessing device and program for processing measurement data accordingto the second embodiment, the peak component and baseline component canbe assuredly excluded, and furthermore, the noise level at each positionon the chromatogram can be calculated. Such a method or device accordingto the second embodiment can be suitably used in the case where thenoise level fluctuates due to the measurement system, e.g. in achromatogram obtained by a gradient analysis in which the baselinecomponent easily fluctuates, causing a corresponding fluctuation in thenoise level.

Both of the first and second embodiments are mere examples and can beappropriately changed in line with the gist of the present invention.

The previously described embodiments have been divided into twoembodiments in order to separately describe their respectiveconfigurations and steps. It is also possible to configure a devicewhich includes the configurations and steps of both of the first andsecond embodiments. With this configuration, it is possible to determinethe noise level at each position on a chromatogram as well as improvethe accuracy of that noise level.

The previously described embodiments are concerned with the case ofprocessing a chromatogram obtained with a liquid chromatograph. Thepresent invention can be used to determine not only the noise level in achromatogram obtained with a liquid chromatograph or gas chromatographbut also in various other kinds of measurement data, such as a spectrumobtained by a spectrometric measurement.

In the previous embodiments, each section where positive valuessuccessively occur or each section where negative values successivelyoccur in the waveform data of high frequency components extracted byusing a second-order difference filter is defined as one segment. Otherkinds of high-pass filters may also be used to extract high frequencycomponents. It should be noted that a section where positive valuessuccessively occur (or a section where negative values successivelyoccur) in the waveform data of high frequency components extracted byusing an n^(th)-order difference filter (where n is an integer equal toor greater than two) corresponds to a section between a local maximumand a local minimum neighboring each other in the waveform data of highfrequency components extracted by using an n+1^(st)-order differencefilter. That is to say, the previously described processing ofmeasurement data can be similarly performed by dividing the waveformdata into segments so that each section between a local maximum and alocal minimum neighboring each other is defined as one segment, insteadof defining each section where positive values successively occur (oreach section where negative values successively occur) as one segment.

REFERENCE SIGNS LIST

-   10, 10 a . . . Measurement Data Processing Device-   11 . . . CPU-   12 . . . Memory-   13 . . . Display Unit-   14 . . . Input Unit-   15 . . . High-Pass Filter-   16 . . . Storage Section-   18, 181 . . . Program for Processing Measurement Data-   18 a . . . Assumed Noise Data Creator-   18 b . . . First Waveform Data Creator-   18 c . . . Segment Divider-   18 d . . . Threshold Setter-   18 e . . . Second Waveform Data Creator-   18 f . . . First Segment Group Creator-   18 g . . . Second Segment Group Creator-   18 h . . . Noise Level Calculator-   18 j . . . Segment Position Determiner-   18 k . . . Target Segment Extractor-   17 . . . Communication Interface

1. A noise level estimation method for estimating a noise levelrepresenting a magnitude of a noise component from measurement datacontaining three components of a peak component, baseline component andnoise component, the method comprising: a) extracting, from assumednoise data purely composed of assumed noise for the measurement data,high frequency noise components by means of a high-pass filter whichreduces frequency components lower than a predetermined frequency,dividing first waveform data which are waveform data of the highfrequency noise components into a plurality of segments so that eachsection where positive values successively occur or each section wherenegative values successively occur in the first waveform data is definedas one segment, or so that each section between a local maximum and alocal minimum neighboring each other in the first waveform data isdefined as one segment, and determining a segment-width threshold basedon a distribution of widths of the plurality of segments; b) extractinghigh frequency measurement components from the measurement data by meansof the high-pass filter, and dividing second waveform data which arewaveform data of the high frequency measurement components into aplurality of segments so that each section where positive valuessuccessively occur or each section where negative values successivelyoccur in the second waveform data is defined as one segment, or so thateach section between a local maximum and a local minimum neighboringeach other in the second waveform data is defined as one segment; c)excluding each segment having a width larger than the threshold from theplurality of segments obtained by dividing the second waveform data, tocreate a first segment group formed by the remaining segments; and d)determining the noise level based on heights or areas of the pluralityof segments included in the first segment group.
 2. The noise levelestimation method according to claim 1, further comprising: e)extracting an outlier from the heights or areas of the plurality ofsegments included in the first segment group by comparing each of theheights or areas with the noise level; f) excluding a segment having theoutlier from the plurality of segments of the first segment group, tocreate a second segment group; g) determining a noise level based on theheights or areas of the plurality of segments included in the secondsegment group.
 3. The noise level estimation method according to claim1, further comprising: h) determining, for each of the plurality ofsegments in the first segment group, a segment position representativeof the segment concerned; i) extracting, for each of the plurality ofsegments in the first segment group, target segments which are segmentshaving their respective segment positions located within a predeterminedrange from the segment position of the segment concerned; and j)determining a noise level at the segment position of the segmentconcerned, based on the heights or areas of the segment concerned andthe target segments.
 4. The noise level estimation method according toclaim 3, further comprising: k) extracting an outlier from the heightsor areas of the target segments by comparing each of the heights orareas with the height or area of the segment concerned; l) excluding asegment having the outlier from the segment concerned or the targetsegments, to create a second segment group; m) determining a noise levelat the segment position of the segment concerned, based on the heightsor areas of the segments included in the second segment group.
 5. Thenoise level estimation method according to claim 2, wherein: the noiselevel is determined after a process including steps of extracting anoutlier from the heights or areas of the segments included in the secondsegment group and removing a segment corresponding to the outlier tonewly create the second segment group is repeated until all outliers areremoved or until a predetermined number of repetitions is reached.
 6. Ameasurement data processing device used for estimating a noise levelfrom measurement data containing three components of a peak component,baseline component and noise component, the device comprising: a) ahigh-pass filter for reducing frequency components lower than apredetermined frequency; b) a storage section for holding asegment-width threshold, the threshold previously determined byextracting, from assumed noise data purely composed of assumed noise forthe measurement data, high frequency noise components by means of thehigh-pass filter, dividing first waveform data which are waveform dataof the high frequency noise components into a plurality of segments sothat each section where positive values successively occur or eachsection where negative values successively occur in the first waveformdata is defined as one segment, or so that each section between a localmaximum and a local minimum neighboring each other in the first waveformdata is defined as one segment, and determining the threshold based on adistribution of widths of the plurality of segments; c) a secondwaveform data acquirer for extracting high frequency measurementcomponents from the measurement data by means of the high-pass filter,and for acquiring second waveform data which are waveform data of thehigh frequency measurement components; d) a segment divider for dividingthe second waveform data into a plurality of segments so that eachsection where positive values successively occur or each section wherenegative values successively occur in the second waveform data isdefined as one segment, or so that each section between a local maximumand a local minimum neighboring each other in the second waveform datais defined as one segment; e) a first segment group creator forexcluding each segment having a width larger than the threshold from theplurality of segments obtained by dividing the second waveform data, tocreate a first segment group; and f) a noise level calculator fordetermining the noise level based on heights or areas of the pluralityof segments included in the first segment group.
 7. A non-transitorycomputer readable medium recording a program for processing measurementdata, used for estimating a noise level from measurement data containingthree components of a peak component, baseline component and noisecomponent, the program characterized by making a computer, provided witha storage section for holding a segment-width threshold and a high-passfilter, function as the second waveform acquirer, the segment divider,the first segment group creator and the noise level calculator describedin claim
 6. 8. The noise level estimation method according to claim 4,wherein: the noise level is determined after a process including stepsof extracting an outlier from the heights or areas of the segmentsincluded in the second segment group and removing a segmentcorresponding to the outlier to newly create the second segment group isrepeated until all outliers are removed or until a predetermined numberof repetitions is reached.